CN110826426B - Vehicle-mounted gesture recognition test system and test method - Google Patents
Vehicle-mounted gesture recognition test system and test method Download PDFInfo
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Abstract
The invention provides a vehicle-mounted gesture recognition test system which comprises a test computer, a five-finger hand grip controller, a five-finger hand grip, a mechanical arm controller, a mechanical arm body, an installation bottom plate and a vehicle-mounted gesture recognition module. Except that the mechanical arm body is connected with the mechanical arm controller to realize communication, other parts are connected with the test computer to realize communication or control. The five-finger grab is mechanically connected with the tail end of the mechanical arm body. The system can simulate human gesture operation actions, can realize manual and full-automatic testing according to a preset testing sequence through the testing computer, covers main testing items of gesture recognition, is applicable to testing of various gesture recognition products, and has the characteristics of strong universality, high efficiency and the like.
Description
Technical Field
The invention belongs to the field of gesture recognition testing technology in the field of automobile human-computer interaction, and particularly relates to a vehicle-mounted gesture recognition testing system and a testing method.
Background
Gesture recognition is widely applied in many fields as a man-machine interaction mode. Especially in the intelligent automobile field, the vehicle-mounted gesture recognition technology can reduce distraction of the driver, so that the driving process is more convenient and safer. The gesture recognition technology used in the automobile is influenced by factors such as space and illumination, and the gesture recognition range, the recognition accuracy and the like are difficult to control. In the prior art, a corresponding universality testing system and method are lacked when a vehicle-mounted gesture recognition test is carried out, and a vehicle-mounted gesture recognition testing system and a vehicle-mounted gesture recognition testing method are urgently needed.
Disclosure of Invention
In view of this, the present invention provides a vehicle-mounted gesture recognition test system to satisfy the requirement of performing gesture recognition function and performance verification during the development process of a vehicle-mounted gesture recognition product. The method can cover main gesture recognition test items, can compatibly complete development, test and evaluation tasks of various gesture recognition products, and has strong universality and easy maintenance.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a vehicle-mounted gesture recognition test system comprises a control platform and a test platform, wherein the test platform comprises an installation bottom plate, a mechanical arm body, a five-finger grip and a gesture recognition module, the control platform comprises a test computer, a mechanical arm and a five-finger grip controller, the test computer is connected with the mechanical arm controller, the five-finger grip controller and the gesture recognition module through communication cables, the mechanical arm body is fixed at a designated position by the installation bottom plate, and the five-finger grip is mechanically connected with the tail end of the mechanical arm body;
the test computer combines digital-analog information of a vehicle interior trim space structure, an installation bottom plate, a mechanical arm body and digital-analog information of a five-finger grip, calculates motion sequences of the mechanical arm body and the five-finger grip, respectively sends the motion sequences to a mechanical arm controller and a five-finger grip controller, the mechanical arm controller and the five-finger grip controller respectively realize various anthropomorphic gesture actions according to formulated motion paths and actions, meanwhile, a gesture recognition module collects external gesture actions and sends the recognition sequences to a test computer, and the test computer analyzes gesture recognition indexes and outputs test results according to real-time pose of the mechanical arm body, the five-finger grip actions and sequence information recognized by the gesture recognition module.
Furthermore, the testing computer can import the interior digital-analog data, the installation bottom plate digital-analog and the mechanical arm body position and pose information of the vehicle, automatically calculate the space motion position and pose sequence of the mechanical arm body and the five-finger grab, and obtain the space motion position and pose sequence by adopting the teaching mode of the robot body and the five-finger grab if the interior digital-analog data information of the tested vehicle is unknown.
Further, the mechanical arm body is a serial 6-degree-of-freedom mechanical arm.
Furthermore, the testing computer is also connected with a database, and the database stores the image and the testing result data.
The invention also aims to provide a test method of the vehicle-mounted gesture recognition test system, which comprises the following steps:
the method comprises the following steps: mounting a mechanical arm body with a five-finger grab at the tail end at the mounting position of a main driving seat of the vehicle through a mounting bottom plate;
step two: importing an interior digital model, an installation bottom plate, a mechanical arm body and five-finger-grasp size and pose information of an interior vehicle, calculating a motion sequence of the mechanical arm body and the five-finger-grasp, or acquiring the motion sequence by a teaching mode of the mechanical arm body and the five-finger-grasp;
step three: control sequences are respectively sent to the mechanical arm controller and the five-finger hand-held controller to realize the actions of the two controllers;
Step four: the gesture recognition module continuously reads external gesture information and sends a recognition sequence to the test computer;
step five: and the test computer continuously records the recognition sequence information of the mechanical arm body, the five-finger grip and the gesture recognition module, analyzes whether the recognition is carried out or not and outputs a test result.
Further, a gesture recognition database is arranged in the test computer, and the establishment method comprises the following steps:
a1) collecting a vehicle and a five-finger-grasp photo library;
a2) collecting a standard gesture picture library;
a3) the vehicle, the five-finger-hand-grab picture library and the standard gesture picture library are respectively segmented by adopting a convolutional neural network, and then the segmented pictures are compared and identified by adopting an RCNN algorithm, so that a standard picture library database with characteristics is established.
Further, in the step (a3), extracting position information of each feature point from each collected static gesture image, analyzing and memorizing a variation trend of the position information of the feature point in each gesture motion sequence, and using the variation trend of the position information of the feature point as a standard for gesture motion recognition, thereby establishing a standard gallery database.
Further, the step (5) further includes comparing the similarity between the gesture recognition module and a preset gesture, and when the similarity reaches a preset range standard, the gesture recognition module generates a comparison result.
Compared with the prior art, the vehicle-mounted gesture recognition test system and the test method provided by the invention have the following advantages:
the gesture recognition system and the gesture recognition method are used for testing the functions and the performances of the gesture recognition module, cover main gesture recognition sequence test items, are suitable for testing various gesture recognition products, and are high in universality and easy to maintain.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the invention without limitation. In the drawings:
FIG. 1 is a schematic diagram of a gesture recognition test system according to the present invention;
FIG. 2 is a schematic diagram of a gesture recognition test system of the present invention;
FIG. 3 is a flow chart of a gesture recognition test method of the present invention;
FIG. 4 is a test sequence diagram in the gesture recognition test method of the present invention. .
Description of reference numerals:
1-testing a computer; 2-a robot arm controller; 3-a five-finger hand controller; 4-a gesture recognition module; 5, mounting a bottom plate; 6-mechanical arm body; 7-grasping with five fingers.
Detailed Description
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "central," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientation or positional relationship indicated in the drawings, which are merely for convenience in describing the invention and to simplify the description, and are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed and operated in a particular orientation, and are therefore not to be construed as limiting the invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the invention, the meaning of "a plurality" is two or more unless otherwise specified.
In the description of the invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted", "connected" and "connected" are to be construed broadly, e.g. as being fixed or detachable or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the creation of the present invention can be understood by those of ordinary skill in the art through specific situations.
The invention will be described in detail with reference to the following embodiments with reference to the attached drawings.
As shown in fig. 1, the vehicle-mounted gesture recognition test system of the invention comprises a test computer 1 and a test platform, wherein the test computer 1 is connected with a manipulator controller 2, a five-finger grip controller 3 and a gesture recognition module 4 through communication cables, the test platform comprises an installation bottom plate 5, a manipulator body 6, a five-finger grip 7 and a gesture recognition module 4, the manipulator body 6 is fixed at a set position by the installation bottom plate 5, and the five-finger grip 7 is mechanically connected with the tail end of the manipulator body 6. The testing computer 1 combines the digital-analog information of the space structure of the interior trim of the vehicle and the digital-analog information of the mounting bottom plate 5, the mechanical arm body 6 and the five-finger grip 7 to calculate the motion sequence of the mechanical arm body 6 and the five-finger grip 7, respectively sends the motion sequence to the mechanical arm controller 2 and the five-finger grip controller 3, respectively realizes various anthropomorphic gesture actions according to the formulated motion path and action by the mechanical arm controller 2 and the five-finger grip controller 3, meanwhile, the gesture recognition module 4 collects external gesture actions and sends recognition sequences to the test computer 1, the test computer 1 comprehensively analyzes indexes such as gesture recognition accuracy, a gesture position recognition range, a gesture posture recognition range and a gesture motion recognition range according to the real-time information of the gesture sequence of the mechanical arm body 6, the motions of the five-finger grips 7 and the recognition sequences of the gesture recognition module 4, and outputs test results.
The testing computer 1 can import the data of the interior decoration digital-analog of the vehicle, the digital-analog of the installation bottom plate 5 and the pose information of the mechanical arm body 6, and automatically calculate the spatial motion pose sequence of the mechanical arm body 6 and the five-finger grip 7. If the data information of the interior decoration digital model of the detected vehicle is unknown, the space motion pose sequence can be obtained by adopting the teaching mode of the robot body 6 and the five-finger grab 7.
The mechanical arm body 6 is a serial 6-degree-of-freedom mechanical arm.
The test computer 1 is connected to a database, which stores images and test result data.
As shown in fig. 3 and 4, the invention further provides a vehicle-mounted gesture recognition test method, wherein the mechanical arm body 6 is mounted at the mounting position of the main driving seat of the vehicle through the mounting bottom plate 5, if the digital-analog information of the interior space structure of the vehicle is known, the test computer 1 imports the digital-analog information of the interior space structure of the vehicle, the mounting bottom plate 5, the mechanical arm body 6 and the digital-analog information of the five-finger grip 7, otherwise, the gesture movable space is obtained by adopting a teaching mode, the motion sequences of the mechanical arm body 6 and the five-finger grip 7 are analyzed and calculated, the generated motion sequences are respectively sent to the mechanical arm controller 2 and the five-finger grip controller 3, the mechanical arm controller 2 and the five-finger grip controller 3 respectively realize various anthropomorphic gesture actions according to the formulated motion path and actions, meanwhile, the gesture recognition module 4 collects the external gesture actions and sends the recognition sequences to the test computer 1, the testing computer 1 comprehensively analyzes indexes such as gesture recognition accuracy, gesture position recognition range, gesture posture recognition range and gesture movement recognition range according to the real-time pose of the mechanical arm body 6, the motions of the five-finger grips 7 and the recognition sequence information of the gesture recognition module 4, and outputs a testing result.
The method of the invention comprises the following steps:
the method comprises the following steps: a mechanical arm body 6 with a five-finger grab 7 at the tail end is arranged at the installation position of a main driving seat of the vehicle through an installation bottom plate 5;
step two: importing an interior digital model of the interior vehicle, a mounting bottom plate 5, a mechanical arm body 6 and the size and pose information of the five-finger grab 7, calculating a motion sequence of the mechanical arm body 6 and the five-finger grab 7, or acquiring the motion sequence by a teaching mode of the mechanical arm body 6 and the five-finger grab 7;
step three: control sequences are respectively sent to the mechanical arm controller 2 and the five-finger hand-held controller 3 to realize the actions of the two;
step four: the gesture recognition module 4 continuously reads external gesture information and sends a recognition sequence to the test computer 1;
step five: the test computer 1 continuously records the identification sequence information of the mechanical arm body 6, the five-finger grab 7 and the gesture identification module 4, comprehensively analyzes gesture motion pose space, motion state, identification and the like, and outputs a test result.
Step six: and storing the test result in the database.
In order to further provide recognition accuracy and efficiency, the test computer is internally provided with a gesture recognition database, and the establishment method comprises the following steps:
a1) Collecting a vehicle and a five-finger-grasp photo library;
a2) collecting a standard gesture picture library;
a3) respectively segmenting a vehicle, a five-finger-hand-grab picture library and a standard gesture picture library by adopting a convolutional neural network, and then comparing and identifying segmented pictures by adopting an RCNN algorithm, thereby establishing a standard picture library database with characteristics; the method also comprises the steps of extracting the position information of each feature point from each collected static gesture image, analyzing and memorizing the change trend of the position information of the feature point in each gesture action sequence, and establishing a standard gallery database by taking the change trend of the position information of the feature point as the standard for gesture action recognition.
The test computer 1 analyzes the gesture recognition rate, the recognition pose range, the movement speed range and the like through a space movement pose algorithm.
The mechanical arm body 6 adopts a Mitsubishi RV-7FM-D series 6-degree-of-freedom mechanical arm, and has the characteristics of high repetition precision, low cost and the like. The robot arm controller 2 uses Mitsubishi CR750-D series. The manipulator 6 receives the command of the test computer 1 through the manipulator controller 2 and drives the five-finger grab 7 to move according to the appointed path.
The test computer 1 adopts a Siemens SIMATIC RACK PC 847C model, and the industrial control computer has the characteristics of strong anti-interference capability, flexible expansion and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the invention, so that any modifications, equivalents, improvements and the like, which are within the spirit and principle of the present invention, should be included in the scope of the present invention.
Claims (6)
1. The utility model provides a vehicle-mounted gesture recognition test system, includes control platform and test platform, its characterized in that: the test platform comprises an installation bottom plate, a mechanical arm body, a five-finger grip and a gesture recognition module, the control platform comprises a test computer, a mechanical arm and a five-finger grip controller, the test computer is connected with the mechanical arm controller, the five-finger grip controller and the gesture recognition module through communication cables, the installation bottom plate fixes the mechanical arm body at an appointed position, and the five-finger grip is mechanically connected with the tail end of the mechanical arm body;
the test computer combines digital-analog information of a vehicle interior trim space structure, an installation bottom plate, a mechanical arm body and digital-analog information of a five-finger grip, calculates motion sequences of the mechanical arm body and the five-finger grip, respectively sends the motion sequences to a mechanical arm controller and a five-finger grip controller, the mechanical arm controller and the five-finger grip controller respectively realize various anthropomorphic gesture actions according to formulated motion paths and actions, simultaneously a gesture recognition module collects external gesture actions and sends the recognition sequences to the test computer, and the test computer analyzes gesture recognition indexes and outputs test results according to real-time pose of the mechanical arm body, the five-finger grip actions and the sequence information of the gesture recognition module;
The test computer is internally provided with a gesture recognition database, and the establishment method comprises the following steps:
a1) collecting a vehicle and a five-finger hand-grabbing photo library;
a2) collecting a standard gesture picture library;
a3) respectively segmenting a vehicle, a five-finger-hand-grab picture library and a standard gesture picture library by adopting a convolutional neural network, and then comparing and identifying segmented pictures by adopting an RCNN algorithm, thereby establishing a standard picture library database with characteristics;
the method also comprises the step of comparing the similarity between the gesture recognition module and a preset gesture, and when the similarity reaches a preset range standard, the gesture recognition module generates a comparison result.
2. The vehicle-mounted gesture recognition test system according to claim 1, characterized in that: the testing computer can lead in the interior digital-analog data, the installation bottom plate digital-analog and the mechanical arm body position and pose information of the vehicle, automatically calculate the space motion position and pose sequence of the mechanical arm body and the five-finger grab, and can also obtain the space motion position and pose sequence by adopting the teaching mode of the robot body and the five-finger grab if the interior digital-analog data information of the tested vehicle is unknown.
3. The vehicle-mounted gesture recognition test system according to claim 1, characterized in that: the mechanical arm body is a serial 6-freedom-degree mechanical arm.
4. The vehicle-mounted gesture recognition test system according to claim 1, characterized in that: the testing computer is also connected with a database, and the database stores the image and the testing result data.
5. A vehicle-mounted gesture recognition test method based on the vehicle-mounted gesture recognition test system of any one of claims 1 to 4, characterized in that: the method comprises the following steps:
the method comprises the following steps: mounting a mechanical arm body with a five-finger grab at the tail end at the mounting position of a main driving seat of the vehicle through a mounting bottom plate;
step two: importing an interior digital model, an installation bottom plate, a mechanical arm body and five-finger-grasp size and pose information of an interior vehicle, calculating a motion sequence of the mechanical arm body and the five-finger-grasp, or acquiring the motion sequence by a teaching mode of the mechanical arm body and the five-finger-grasp;
step three: control sequences are respectively sent to the mechanical arm controller and the five-finger hand-held controller to realize the actions of the two controllers;
step four: the gesture recognition module continuously reads external gesture information and sends a recognition sequence to the test computer;
step five: the testing computer continuously records the recognition sequence information of the mechanical arm body, the five-finger grab and the gesture recognition module, analyzes whether the recognition is carried out or not and outputs a testing result;
The test computer is internally provided with a gesture recognition database, and the establishment method comprises the following steps:
a1) collecting a vehicle and a five-finger-grasp photo library;
a2) collecting a standard gesture picture library;
a3) respectively segmenting a vehicle, a five-finger-hand-grab picture library and a standard gesture picture library by adopting a convolutional neural network, and then comparing and identifying segmented pictures by adopting an RCNN algorithm, thereby establishing a standard picture library database with characteristics;
and step five, comparing the similarity between the gesture recognition module and a preset gesture, wherein when the similarity reaches a preset range standard, the gesture recognition module generates a comparison result.
6. The vehicle-mounted gesture recognition test method according to claim 5, characterized in that: in step a 3), extracting position information of each feature point from each collected static gesture image, analyzing and memorizing the variation trend of the position information of the feature point in each gesture action sequence, and using the variation trend of the position information of the feature point as the standard for gesture action recognition, thereby establishing a standard database.
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